Agriculturalists have long understood that varying the products (such as fertilizers, pesticides, and other agricultural inputs) applied at different locations within a field, and that varying the rates at which such products are applied at different locations within a field, can affect crop yield. More generally, the term “system” is used within agriculture to refer to a collection of one or more products, practices, and application rates. It has long been known that varying the system from one location to another within a field can affect crop yield. Traditional agriculture, however, has lacked the tools to determine with high accuracy which product, rate, or system should be applied at different locations within a field to optimize the yield within those locations.
In response to this problem, agriculturalists have begun to develop techniques for “precision agriculture,” which aims to use computers and other information technology—such as global positioning systems (GPS) and geographic information systems (GIS)—to facilitate the application of appropriate rates of agricultural inputs at specific locations. Precision agriculture technologies have spread rapidly in the Midwestern United States, with yield monitoring equipment being used by farmers to monitor the yield of 36% of corn and 29% of soybean area harvested in 2001 and 2002. In 2009, 57% of service providers used yield monitors (31% without GPS and 26% with GPS). Precision agriculture has already begun to produce results which demonstrably increase profitability.
Better understanding of system effects within fields utilizing precision agriculture can be achieved via the use of spatial analysis, which is the process of accounting for the impact of natural variability, deliberate interventions (such as application of pesticides and/or fertilizers), and/or man-made or man-caused phenomena (such as cropping history) on yield in commercial agriculture crop production fields. The science of agriculture spatial analysis is relatively new, and heretofore, it has required a significant amount of human intervention at each decision node, such as entering and accounting for field variables, interpreting diagnostics at intermediate steps, and accounting for the attendant geo-referenced crop yield.
Spatial analysis in particular utilizes geo-referenced, or precision agriculture yield monitor technology. One of the leading barriers to farmers adopting yield monitor technology is the lack of complementary services in data analysis. Without data analysis services, farmers have little incentive to adopt yield-monitor technology. One of the leading uses of yield monitor technology (which represents the third-highest use for corn and soybean farmers and the highest use for cotton farmers) is to conduct on-farm experiments. Several decision nodes exist in the process of properly analyzing on-farm experiment data, such as collecting data and interpreting the quantitative results.
Even with sufficient equipment and machinery to implement on-farm experiments and collect site-specific yield and supporting information, the lack of qualified analysts able to provide services for a fee that farmers are willing to pay exists. The few individuals schooled in the art of crop yield spatial analysis charge a fee of approximately $500/field to conduct such an analysis. As a result, very few farmers avail themselves of the enhanced information that spatial analysis can provide.
What is needed, therefore, are improved techniques for performing spatial analysis quickly and inexpensively.